Digital Twin Solutions Engineer Job Vacancy in Bloemfontein, South Africa – Advanced Manufacturing

Siemens South Africa

Bloemfontein

Sur place

ZAR 1 700 - 2 600

Plein temps

14 jours+

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Avantages offerts par ce poste

Medical aid
Life insurance
Retirement plan
Paid leave
Wellness initiatives
Training resources

Résumé du poste

Siemens South Africa, Bloemfontein, seeks a Digital Twin Solutions Engineer with 5+ years in digital twin development, simulation, or related fields.

You will design, implement, and optimize digital twin models for manufacturing assets, integrating sensors, PLC data, and ERP information on Siemens' industrial IoT platform.

Qualifications

  • Bachelor's degree in Mechanical Engineering, Electrical Engineering, Computer Science, or related field.
  • 5+ years of experience in digital twin development, simulation, or advanced manufacturing solutions.
  • Experience delivering end-to-end digital twin projects in industrial settings.

Responsabilités

  • Develop and validate high-accuracy digital twin models for manufacturing equipment, production lines, and plant facilities.
  • Integrate sensor data, PLC signals, and ERP information into real-time simulation environments.
  • Collaborate with cross-functional teams to define use cases, performance metrics, and success criteria for digital twin deployments.
  • Design and implement predictive algorithms for maintenance scheduling and process optimization.
  • Provide technical guidance and training to client engineering teams on digital twin best practices.
  • Document solution architecture, configuration settings, and validation results.
  • Stay abreast of industry trends and Siemens tools to enhance offerings.

Connaissances

3D modelling
Python
C++
MATLAB
OPC-UA
MQTT
Azure
AWS
Manufacturing processes
Communication
Stakeholder management

Formation

Bachelor's degree in Mechanical Engineering
Bachelor's degree in Electrical Engineering
Bachelor's degree in Computer Science

Outils

Siemens NX
Simcenter
ANSYS

Description du poste

Position:Digital Twin Solutions Engineer

Company:Siemens South Africa

Location:Bloemfontein, South Africa

Experience:5+ years in digital twin development, simulation, or related fields

Education:Bachelor's degree in Mechanical Engineering, Computer Science, or related discipline

Employment Type:Full-time

Industry:Advanced Manufacturing

Department:Engineering

Salary:SSP 600,000 - 900,000 per annum

Vacancies:1

Company Overview

Siemens South Africa is a leading global technology powerhouse, delivering innovative solutions across energy, automation, and digital industries. With a strong presence in South Africa for over a century, Siemens combines cutting-edge research with local expertise to drive the nation’s industrial transformation. The company’s commitment to sustainability, smart manufacturing, and Industry 4.0 positions it as a preferred employer for professionals seeking to shape the future of production. As part of Siemens’ worldwide network, the Bloemfontein office collaborates closely with research centres, universities, and partner firms to develop next-generation digital solutions that enhance efficiency, reduce waste, and improve product quality.

Employees at Siemens enjoy a collaborative culture that encourages continuous learning, cross-functional teamwork, and a focus on delivering measurable impact for customers. The organisation's values of responsibility, excellence, and innovation are reflected in every project, making it an ideal environment for engineers who thrive on solving complex challenges. Siemens South Africa is also recognised for its robust corporate social responsibility programmes, supporting STEM education and community development across the country.

Job Overview

The Digital Twin Solutions Engineer will lead the design, implementation, and optimisation of digital twin models for manufacturing assets and processes. Working within the Advanced Manufacturing division, you will translate physical system data into high-fidelity virtual replicas that enable predictive maintenance, performance optimisation, and rapid prototyping. This role requires close collaboration with product designers, data scientists, and operations teams to ensure that digital twins deliver actionable insights and tangible business value.

As part of your responsibilities, you will engage with customers to understand their operational challenges, propose tailored digital twin strategies, and oversee the end-to-end deployment of solutions on Siemens' industrial IoT platform. You will also contribute to the continuous improvement of Siemens' digital twin framework, incorporating emerging technologies such as AI-driven analytics, edge computing, and augmented reality visualisations.

Key Responsibilities
  • Develop and validate high-accuracy digital twin models for manufacturing equipment, production lines, and plant facilities.
  • Integrate sensor data, PLC signals, and ERP information into real-time simulation environments.
  • Collaborate with cross-functional teams to define use cases, performance metrics, and success criteria for digital twin deployments.
  • Design and implement predictive algorithms that leverage digital twin data for maintenance scheduling and process optimisation.
  • Provide technical guidance and training to client engineering teams on digital twin best practices.
  • Document solution architecture, configuration settings, and validation results for internal knowledge bases.
  • Stay abreast of industry trends, emerging standards, and new Siemens tools to continuously enhance solution offerings.
Required Skills
  • Proficiency in 3D modelling and simulation tools such as Siemens NX, Simcenter, or ANSYS.
  • Strong programming skills in Python, C++, or MATLAB for data processing and algorithm development.
  • Experience with industrial IoT platforms, OPC-UA, MQTT, and cloud services (Azure, AWS).
  • Solid understanding of manufacturing processes, control systems, and equipment lifecycle management.
  • Excellent problem-solving abilities and the capacity to translate complex technical concepts into clear business outcomes.
  • Effective communication and stakeholder management skills.
Education

A Bachelor's degree in Mechanical Engineering, Electrical Engineering, Computer Science, or a related field is required. Advanced degrees or certifications in simulation, data analytics, or Industry 4.0 technologies are highly desirable.

Experience

Minimum of five years' experience in digital twin development, systems engineering, or advanced manufacturing solutions. Proven track record of delivering end-to-end digital twin projects in an industrial setting is essential.

Salary

The role offers a competitive salary range of SSP 600,000 - 900,000 per annum, commensurate with experience and qualifications. Performance-based bonuses and incentives are also part of the remuneration package.

Benefits
  • Comprehensive medical aid and life insurance coverage.
  • Retirement savings plan with company matching contributions.
  • Generous paid leave, including annual, sick, and parental leave.
  • Employee assistance programme and wellness initiatives.
  • Access to Siemens global training resources and certification programmes.
Training
  • Onboarding programme covering Siemens' digital twin framework and industrial IoT ecosystem.
  • Continuous professional development through Siemens Learning Campus, webinars, and workshops.
  • Opportunities to attend international conferences and industry exhibitions.
Working Environment

Based in Bloemfontein, the role offers a modern office environment equipped with state-of-the-art collaboration spaces, high-speed connectivity, and flexible work-from-home options. The team culture promotes innovation, knowledge sharing, and a strong focus on work-life balance.

Equal Opportunity Statement

Siemens South Africa is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees, regardless of gender, race, disability, or background. All qualified applicants will receive consideration for employment without discrimination.

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